Article deduction apparatus, article deduction method, and program

ABSTRACT

An article information deduction apparatus ( 10 ) includes an acquisition unit ( 110 ) and an output unit ( 120 ). The acquisition unit ( 110 ) acquires data based on a change in a detected value of a weight sensor ( 30 ) (hereinafter described as weight change data). For example, the acquisition unit ( 110 ) determines data acquired by chronologically arranging data acquired from the weight sensor ( 30 ) as weight change data. Further, the acquisition unit ( 110 ) acquires data indicating a movement of a hand of a person positioned in a shelf-front space (hereinafter described as movement data). For example, the acquisition unit ( 110 ) acquires data acquired by chronologically arranging data output from a depth sensor ( 40 ) to the article information deduction apparatus ( 10 ) as movement data. The output unit ( 120 ) outputs article determination information of the article deduced to be taken out by the hand of the person positioned in the shelf-front space, by using the weight change data and the movement data.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 17/434,813 filed on Aug. 30, 2021, which is aNational Stage Entry of international application PCT/JP2020/006860filed on Feb. 20, 2020, which claims the benefit of priority fromJapanese Patent Application 2019-037829 filed on Mar. 1, 2019, thedisclosures of all of which are incorporated in their entirety byreference herein.

TECHNICAL FIELD

The present invention relates to an article deduction apparatus, anarticle deduction method, and a program.

BACKGROUND ART

In recent years, technological development for reduction of labor at astore, a factory, and the like is under way. For example, PTL 1describes, in work of boxing a plurality of types of articles taken outfrom an inventory shelf as one set, measuring the total weight ofarticles 5 stored in the inventory shelf and determining whether toissue a warning by using the measurement result.

Further, PTL 2 describes, in order to manage handling of articles,generating inventory data by using a result of processing a capturedimage of a bar code or a QR code (registered trademark) of an article.Inventory data are information indicating handling status of an articleand, for example, are information correlating identification informationof an article an image of which is captured, a date and time whenchecking of the article is performed, a location where the article isinstalled, and identification information of a user handling the articlewith one another.

CITATION LIST Patent Literature

-   PTL 1: Japanese Patent Application Publication No. 2017-218289-   PTL 2: Japanese Patent Application Publication No. 2017-210310

SUMMARY OF INVENTION Technical Problem

In order to promote reduction of labor, it is preferable to enableautomatic determination of an article taken out from a shelf. An objectof the present invention is to improve determination precision of anarticle taken out from a shelf.

Solution to Problem

The present invention provides an article deduction apparatus including:

-   -   an acquisition unit that acquires weight change data being data        based on a change in a detected value of a weight sensor        provided on a shelf on which a plurality of articles can be        placed and movement data indicating a movement of a hand of a        person positioned in a shelf-front space being a space in front        of the shelf; and    -   an output unit that outputs article determination information of        the article deduced to be taken out by the hand, by using the        weight change data and the movement data.

The present invention provides an article deduction method including, bya computer:

-   -   acquiring weight change data being data based on a change in a        detected value of a weight sensor provided on a shelf on which a        plurality of articles can be placed and movement data indicating        a movement of a hand of a person positioned in a shelf-front        space being a space in front of the shelf; and    -   outputting article determination information of the article        deduced to be taken out by the hand, by using the weight change        data and the movement data.

The present invention provides a program causing a computer to have:

-   -   a function of acquiring weight change data being data based on a        change in a detected value of a weight sensor provided on a        shelf on which a plurality of articles can be placed and        movement data indicating a movement of a hand of a person        positioned in a shelf-front space being a space in front of the        shelf; and    -   a function of outputting article determination information of        the article deduced to be taken out by the hand, by using the        weight change data and the movement data.

Advantageous Effects of Invention

The present invention improves determination precision of an articletaken out from a shelf.

BRIEF DESCRIPTION OF DRAWINGS

The aforementioned object, other objects, features and advantages willbecome more apparent by the following preferred example embodiments andaccompanying drawings.

FIG. 1 is a diagram illustrating a functional configuration of anarticle information deduction apparatus according to a first exampleembodiment along with a use environment of the article informationdeduction apparatus.

FIG. 2 is a diagram illustrating an example of data stored by a shelfspace allocation information storage unit.

FIG. 3 is a block diagram illustrating a hardware configuration of thearticle information deduction apparatus illustrated in FIG. 1 .

FIG. 4 is a flowchart for illustrating an operation example of thearticle information deduction apparatus.

FIG. 5 is a flowchart for illustrating details of processing performedin Step S104.

FIG. 6 is a diagram illustrating a layout example of shelves and weightsensors according to a modified example.

FIG. 7 is a diagram illustrating a functional configuration of anarticle information deduction apparatus according to a second exampleembodiment along with a use environment of the article informationdeduction apparatus.

FIG. 8 is a plan view for illustrating a layout of weight sensorsaccording to a third example embodiment.

FIG. 9 is a flowchart for illustrating details of determinationprocessing of an article (Step S104 in FIG. 4 ) in the third exampleembodiment.

FIG. 10 is a diagram illustrating a functional configuration of anarticle information deduction apparatus according to a fourth exampleembodiment along with a use environment of the article informationdeduction apparatus.

FIG. 11 is a flowchart for illustrating details of Step S104 in thefourth example embodiment.

FIG. 12 is a diagram illustrating a functional configuration of anarticle information deduction apparatus according to a fifth exampleembodiment along with a use environment of the article informationdeduction apparatus.

FIG. 13 is a flowchart for illustrating an operation example of thearticle information deduction apparatus according to the fifth exampleembodiment.

EXAMPLE EMBODIMENT

Example embodiments of the present invention will be described below byusing drawings. Note that, in every drawing, similar components aregiven similar signs, and description thereof is omitted as appropriate.

First Example Embodiment

FIG. 1 is a diagram illustrating a functional configuration of anarticle information deduction apparatus 10 according to a first exampleembodiment along with a use environment of the article informationdeduction apparatus 10. The article information deduction apparatusaccording to the example embodiment is an apparatus deducing an article200 taken out from a shelf 20 by a person and is used along with aweight sensor 30 and a depth sensor 40. The shelves 20 in the diagramare illustrated in a state of being viewed from the side.

A plurality of articles 200 can be placed on a shelf 20. For example,when a shelf 20 is placed in a store or a distribution center, the shelf20 is a product shelf, an article 200 is a product, and a person takingout an article 200 is a customer or a clerk (employee). Further, when ashelf 20 is placed in a pharmacy, the shelf 20 is a medicine shelf, anarticle 200 is a medicine, and a person taking out an article 200 is apharmacist.

According to the present example embodiment, an article 200 is placed oneach of a plurality of tiers of shelves 20. A plurality of types ofarticles 200 are placed on the plurality of tiers of shelves 20. Then,for each article 200, a shelf 20 on which the article 200 is placed ispredetermined. Therefore, when a shelf 20 from which an article 200 istaken out is identified, the type of the article 200 can be deduced.Note that there may be one shelf 20.

A detection range of the depth sensor 40 includes a space in front ofshelves 20 (hereinafter described as a shelf-front space), and the depthsensor 40 generates data indicating a movement of a hand of a personpositioned in the shelf-front space. For example, the depth sensor 40 isplaced above the shelf-front space but may be placed on side of theshelf-front space or may be placed below the shelf-front space. Then,the depth sensor 40 generates data indicating the position of the handin an x-y plane (that is, a horizontal plane) and the position of thehand in a z-direction (that is, a height direction) and outputs the datato the article information deduction apparatus 10. Therefore, when aperson puts a hand into a shelf 20, the article information deductionapparatus 10 can determine the shelf 20 by using data generated by thedepth sensor 40. For example, a stereo camera may be used in the depthsensor 40 or light detection and ranging (LiDAR) may be used. Further,the article information deduction apparatus 10 may generate dataindicating the position of a hand by processing output data from thedepth sensor 40.

Further, an article 200 taken out from a shelf 20 can be deduced bydetecting decrease in the total weight of articles placed on the shelf20 by a reference value or greater, that is, decrease in the weight ofthe shelf 20 by the reference value or greater. Specifically, a weightsensor 30 detects the total weight of a shelf 20. The detected value ofthe weight sensor 30 is output to the article information deductionapparatus 10 along with weight sensor identification informationassigned to the weight sensor 30. Then, by using the weight sensoridentification information, the article information deduction apparatus10 can deduce the type of the article 200 being taken out.

Functional Configuration Example

The article information deduction apparatus 10 includes an acquisitionunit 110 and an output unit 120.

The acquisition unit 110 acquires data based on changes in the detectedvalue of the weight sensor 30 (hereinafter described as weight changedata). For example, the acquisition unit 110 generates weight changedata by chronologically arranging data acquired from a weight sensor 30.Note that a data processing apparatus generating weight change data byusing data generated by a weight sensor 30 may be provided outside thearticle information deduction apparatus 10. In this case, theacquisition unit 110 acquires weight change data from the dataprocessing apparatus.

Further, the acquisition unit 110 acquires data indicating a movement ofa hand of a person positioned in a shelf-front space (hereinafterdescribed as movement data). For example, the acquisition unit 110generates movement data by chronologically arranging data output fromthe depth sensor 40 to the article information deduction apparatus 10.

The output unit 120 outputs article determination information of anarticle deduced to be taken out by a hand of a person positioned in ashelf-front space by using weight change data and movement data. Thearticle information deduction apparatus 10 according to the presentexample embodiment includes a shelf space allocation information storageunit 130. For each shelf 20, the shelf space allocation informationstorage unit 130 stores article determination information fordetermining an article placed in the shelf 20. For example, the outputunit 120 determines a shelf 20 on which a product being taken out isplaced, reads article determination information related to thedetermined shelf 20 from the shelf space allocation information storageunit 130, and outputs the read article determination information. Forexample, article determination information is an ID (or may be codeinformation) assigned to an article or a name of the article (such as aproduct name).

FIG. 2 is a diagram illustrating an example of data stored by the shelfspace allocation information storage unit 130. For each piece ofinformation indicating the position of a shelf 20 (hereinafter describedas shelf position information), the shelf space allocation informationstorage unit 130 according to the present example embodiment storesweight sensor identification information of a weight sensor 30 installedon the shelf 20, article determination information of an article 200placed at the position, and threshold value information. The shelfposition information includes information for determining the height ofthe shelf 20 (such as the height from the floor or the number of tiersfrom the bottom). The threshold value information is a value assumed tobe a decrement of the detected value of the weight sensor 30 when anarticle 200 is taken out from the shelf and, for example, set to a valueequal to or greater than 90% and equal to or less than 110% of theweight of the article 200. A threshold value indicated by the thresholdvalue information is used by the output unit 120, as will be describedlater.

Hardware Configuration Example

FIG. 3 is a block diagram illustrating a hardware configuration of thearticle information deduction apparatus 10 illustrated in FIG. 1 . Thearticle information deduction apparatus 10 includes a bus 1010, aprocessor 1020, a memory 1030, a storage device 1040, an input-outputinterface 1050, and a network interface 1060.

The bus 1010 is a data transmission channel for the processor 1020, thememory 1030, the storage device 1040, the input-output interface 1050,and the network interface 1060 to transmit and receive data to and fromone another. Note that the method of interconnecting the processor 1020and other components is not limited to a bus connection.

The processor 1020 is a processor provided by a central processing unit(CPU), a graphics processing unit (GPU), or the like.

The memory 1030 is a main storage provided by a random access memory(RAM) or the like.

The storage device 1040 is an auxiliary storage provided by a hard diskdrive (HDD), a solid state drive (SSD), a memory card, a read onlymemory (ROM), or the like. The storage device 1040 stores programmodules providing functions of the article information deductionapparatus 10 (such as the acquisition unit 110 and the output unit 120).By the processor 1020 reading each program module into the memory 1030and executing the program module, each function related to the programmodule is provided.

The input-output interface 1050 is an interface for connecting thearticle information deduction apparatus 10 to various types ofinput-output equipment.

The network interface 1060 is an interface for connecting the articleinformation deduction apparatus 10 to a network. For example, thenetwork is a local area network (LAN) or a wide area network (WAN). Themethod of connecting the network interface 1060 to the network may be awireless connection or a wired connection.

Then, the article information deduction apparatus 10 is connected torequired equipment (for example, sensors such as a weight sensor 30 andthe depth sensor 40) through the input-output interface 1050 or thenetwork interface 1060.

Operation Example

FIG. 4 is a flowchart for illustrating an operation example of thearticle information deduction apparatus 10. In the example illustratedin the diagram, a weight sensor 30 always continues transmitting dataand weight sensor identification information to the article informationdeduction apparatus 10. Further, the depth sensor 40 also alwayscontinues transmitting data to the article information deductionapparatus 10. The acquisition unit 110 continues acquiring the data,that is, weight change data and movement data. Further, the acquisitionunit 110 continues causing a storage to store acquired data as needed.

The output unit 120 analyzes the detected values of weight sensors 30acquired by the acquisition unit 110 and determines weight sensoridentification information of a weight sensor the detected value (thatis, the weight) of which has decreased by a reference value or greater(Step S102). For example, the reference value is stored in the shelfspace allocation information storage unit 130 as illustrated in FIG. 2 .Then, the output unit 120 performs determination processing of anarticle by using the weight sensor identification information determinedin Step S102 and the detected value of the depth sensor 40 (Step S104).

FIG. 5 is a flowchart for illustrating details of the processingperformed in Step S104. First, the output unit 120 reads shelf positioninformation related to the weight sensor identification informationdetermined in Step S102 from the shelf space allocation informationstorage unit 130 (Step S202). Next, the output unit 120 analyzes thedata output by the depth sensor 40 and detects the height of a handinserted into a shelf 20 (Step S204).

Next, the output unit 120 determines whether a relation between theheight of the hand detected in Step S204 and the shelf positioninformation read in Step S202 satisfies a criterion (Step S206). Forexample, when the height of the hand detected in Step S204 is betweenthe height indicated by the shelf position information and the height ofa shelf 20 above the shelf, the output unit 120 determines that thecriterion is satisfied. Note that the criterion may be stored in theshelf space allocation information storage unit 130 for each shelf 20.In this case, the output unit 120 reads and uses a criterion associatedwith the shelf position information determined in Step S102. Further,the shelf space allocation information storage unit 130 may store arange within which the height of a hand inserted into the shelf 20 mayfall, in place of the shelf position information. In this case, theoutput unit 120 determines whether a height newly acquired by the depthsensor 40 falls within the range.

When the relation between the height of the hand and the shelf positioninformation satisfies the criterion (Step S206: Yes), the output unit120 deduces the article 200 taken out by the person, by reading articledetermination information related to the weight sensor identificationinformation determined in Step S102 from the shelf space allocationinformation storage unit 130 (Step S208). Then, the output unit 120outputs the read article determination information.

On the other hand, when the relation between the height of the hand andthe shelf position information does not satisfy the criterion (StepS206: No), the output unit 120 performs alert processing. For example,the alert processing refers to displaying a predetermined screen on aterminal of a person in charge of the article 200 (such as a clerk whenthe shelf 20 is in a store) (Step S210). Note that data generated by thedepth sensor 40, and/or an image captured by a first image capture unit70 and/or an image captured by a second image capture unit 80 describedin example embodiments to be described later may be transmitted to theterminal of the person in charge, along with the alert processing or inplace of the alert processing. In this case, the person in charge maydeduce the article 200 being taken out by checking the image or the likeand transmit the result to the output unit 120 through the terminal.

Note that the output unit 120 according to the present exampleembodiment may first detect that the position of a hand is a heightrelated to one of the shelves 20 and read article determinationinformation related to the shelf 20 when a weight change of the shelf 20subsequently satisfies the criterion.

Modified Example 1

FIG. 6 is a diagram illustrating a layout example of shelves 20 andweight sensors 30, according to a modified example. In the diagram, theshelves 20 are illustrated in a state of being viewed from the front. Inthe example illustrated in the diagram, at least a shelf 20 in one tierincludes a plurality of partial areas 22. An article 200 different fromthat in another partial area 22 is placed in at least one of theplurality of partial areas 22. A weight sensor 30 is provided for eachpartial area 22. Then, for each of the plurality of partial areas 22,the shelf space allocation information storage unit 130 stores theinformation illustrated in FIG. 2 , that is, shelf position information,weight sensor identification information, article determinationinformation, and threshold value information.

Further, a shelf-front space is set for each partial area 22, and adepth sensor 40 is also provided for each partial area 22. Each of aplurality of depth sensors 40 stores depth sensor identificationinformation for distinguishing the depth sensor 40 from another depthsensor 40. Then, the depth sensor 40 transmits the depth sensoridentification information to the article information deductionapparatus 10 along with data. For each piece of shelf positioninformation, the shelf space allocation information storage unit 130stores depth sensor identification information of a depth sensor 40related to the shelf position. By using a combination of weight sensoridentification information and depth sensor identification informationstored in the shelf space allocation information storage unit 130, thearticle information deduction apparatus 10 determines a combination ofdata transmitted from a depth sensor 40 and data transmitted from aweight sensor 30.

Then, for each combination of data, in other words, on a per partialarea 22 basis, the article information deduction apparatus 10 performsthe processing illustrated in FIG. 4 and FIG. 5 . The present modifiedexample enables deduction of an article 200 taken out by a person evenwhen a plurality of types of articles 200 are placed on shelves 20 atthe same height.

As described above, when the position of a shelf 20 in which a weightchange is detected and the height of a hand determined by the depthsensor 40 satisfy a criterion, an article 200 on the shelf 20 isdetermined to be taken out by the hand, according to the present exampleembodiment. Accordingly, determination precision of an article 200 takenout from a shelf 20 is improved.

Second Example Embodiment Functional Configuration Example

FIG. 7 is a diagram illustrating a functional configuration of anarticle information deduction apparatus 10 according to the presentexample embodiment along with a use environment of the articleinformation deduction apparatus 10 and corresponds to FIG. 1 in thefirst example embodiment. The article information deduction apparatus 10according to the present example embodiment has a configuration similarto that of the article information deduction apparatus 10 according tothe first example embodiment except for the following points.

First, the article information deduction apparatus 10 acquires personidentification information of a person existing in a shelf-front spacein front of shelves 20 from a person tracking apparatus 50.

For example, by analyzing images sent from a plurality of image captureunits image capture ranges of which are locations different from oneanother, the person tracking apparatus generates, for each person,traffic line information indicating a traffic line of the person. Then,the person tracking apparatus 50 stores the traffic line information inassociation with person identification information. For example, personidentification information is a feature value acquired from an image ofa person. Further, when shelves 20 are installed in a store, personidentification information may be a customer ID such as a membershipnumber. Then, when a person stays in a shelf-front space in front ofshelves 20 for a certain time, the person tracking apparatus 50 outputsperson identification information of the person to the articleinformation deduction apparatus 10.

Then, the article information deduction apparatus 10 includes a storageprocessing unit 140. The storage processing unit 140 causes a registeredarticle storage unit 60 to store article determination informationacquired by an output unit 120 in Step S208 in FIG. 5 in associationwith person identification information acquired from the person trackingapparatus 50.

For example, when shelves 20 are installed in a store, the articleinformation deduction apparatus 10 and the registered article storageunit 60 can be used as a product registration apparatus in a point ofsale system (POS) and/or a store server. Then, a checkout apparatus inthe POS performs checkout processing by using information stored by theregistered article storage unit 60.

For example, the person tracking apparatus 50 stores a feature value ofthe face of a customer entering the store. In this case, for example,the person tracking apparatus 50 acquires an image from an image captureapparatus an image capture range of which includes an entrance of thestore and, by processing the image, acquires and stores a feature valueof the face of the customer.

Then, as described above, the person tracking apparatus 50 generatestraffic line information of the customer by using the feature value.Traffic line information is associated with a feature value or acustomer ID associated with the feature value. Further, the storageprocessing unit 140 in the article information deduction apparatus 10causes the registered article storage unit 60 to store articledetermination information of a product taken out by a customer inassociation with a feature value (or a customer ID associated with thefeature value) of the customer. The processing is repeated until thecustomer performs checkout processing, and therefore when the customertakes out a plurality of products, the registered article storage unitstores article determination information of the plurality of products inassociation with the feature value (or the customer ID associated withthe feature value) of the customer.

Further, by using a customer terminal, the customer can read informationstored by the registered article storage unit 60. For example, thecustomer terminal transmits a feature value (or a customer ID) of thecustomer to the storage processing unit 140. The storage processing unit140 reads article determination information associated with thetransmitted feature value (or customer ID) from the registered articlestorage unit 60 and transmits the article determination information as aproduct list to the customer terminal. At this time, the articledetermination information may be converted into a product name by usinga database. Further, the price of the product may be sent along with thearticle determination information (or product name). In the case of thelatter, the total price of registered products may be furthertransmitted to the customer terminal.

Then, the customer terminal displays the transmitted product list. Forexample, the screen includes an input button for causing a checkout tobe made.

Then, for example, by operating the customer terminal, the customertransmits information to the effect that a checkout of the product is tobe made to the checkout apparatus along with the feature value (orcustomer ID) of the customer. The checkout apparatus reads articledetermination information related to the received feature value (orcustomer ID) from the registered article storage unit 60 and performscheckout processing by using the read information. The checkoutapparatus subsequently generates an electronic receipt and transmits theelectronic receipt to the customer terminal. Note that the checkoutapparatus may be built into the article information deduction apparatus10.

Note that the information to the effect that a checkout of the productis to be made may be input from a terminal installed in the store. Inthis case, the terminal may generate a feature value by capturing animage of the face of the customer and transmit the feature value to thecheckout apparatus.

Further, when shelves 20 are installed in a distribution center or apharmacy, a person taking out an article 200 can be checked by usinginformation stored by the registered article storage unit 60.

Note that while the registered article storage unit 60 resides outsidethe article information deduction apparatus 10 in the exampleillustrated in FIG. 7 , the registered article storage unit 60 may bepart of the article information deduction apparatus 10. Further, forexample, person determination information may be input by a person byusing an input apparatus (such as a card reader) installed on the shelf20.

The present example embodiment also improves determination precision ofan article 200 taken out from a shelf 20, similarly to the first exampleembodiment. Further, the registered article storage unit 60 storesarticle determination information of an article 200 taken out by aperson in association with person identification information of theperson. Accordingly, who takes out which article 200 can be checked.

Third Example Embodiment Functional Configuration Example

FIG. 8 is a plan view for illustrating a layout of weight sensors 30according to the present example embodiment. A plurality of weightsensors 30 according to the present example embodiment are providedseparately from one another on one shelf 20 or in one partial area 22(hereinafter described as on one shelf 20). In the example illustratedin the diagram, a shelf 20 is rectangular, and a weight sensor 30 isprovided at each of the four corners of the shelf 20.

Then, weight change data used by an output unit 120 are based on changesin the detected values of the plurality of weight sensors 30. As anexample, weight change data indicate changes in the detected values ofthe plurality of weight sensors 30 over time. Then, when changes in thedetected values of the plurality of weight sensors 30 satisfy acriterion, the output unit 120 in an article information deductionapparatus 10 determines that an article 200 on the shelf 20 is takenout. For example, when the total value of decrements of the detectedvalues of the plurality of weight sensors 30 satisfy a criterion, theoutput unit 120 determines that an article 200 is taken out. At thistime, by using decrements of the detected values of the plurality ofweight sensors 30, the output unit 120 determines the position in theshelf 20 at which an article 200 is taken out.

Note that pieces of weight sensor identification information of aplurality of weight sensors 30 provided on the same shelf 20 areassociated with one another in a shelf space allocation informationstorage unit 130 and are managed as a set of weight sensors 30. Forexample, pieces of weight sensor identification information of aplurality of weight sensors 30 provided on the same shelf 20 areassociated with information distinguishing the shelf 20 from anothershelf 20, such as shelf position information. Therefore, by usinginformation stored by the shelf space allocation information storageunit 130, the output unit 120 can perform the aforementioned processing.

Operation Example

The article information deduction apparatus 10 first determines a set ofweight sensors changes in the detected values of which satisfy acriterion (Step S102 in FIG. 4 ). Next, by using the detection result ofthe determined set of weight sensors 30, the article informationdeduction apparatus 10 executes determination processing of an article(Step S104 in FIG. 4 ).

FIG. 9 is a flowchart for illustrating details of the determinationprocessing of an article (Step S104 in FIG. 4 ) according to the presentexample embodiment. First, the output unit 120 reads shelf positioninformation related to weight sensor identification information of theweight sensors 30 determined in Step S102 (Step S222).

Next, by using changes in the detected values of the plurality of weightsensors 30, the output unit 120 deduces a position in the shelf 20 wherea weight change has occurred, that is, a position where an article 200being taken out has been placed. For example, the output unit 120assumes a variation in each weight sensor 30 as a weight and deduces aposition being the barycenter of the weights to be the positiondescribed above (Step S224).

Further, by using data transmitted from a depth sensor 40, the outputunit 120 determines the height of a hand and determines the direction inwhich the hand extends. For example, when a depth sensor 40 outputs adepth map two-dimensionally indicating height information, the outputunit 120 determines the height and direction of the hand by using thedepth map (Step S226).

Then, the output unit 120 determines whether a relation between theheight of the hand and the shelf position information satisfies acriterion and a relation between the direction of the hand and theposition of the article 200 determined in Step S224 satisfies acriterion. The determination of whether a relation between the height ofthe hand and the shelf position information satisfies a criterion issimilar to the determination described in Step S206 in FIG. 5 . Withregard to a relation between the direction of the hand and the positionof the article 200, for example, when the direction of the hand overlapsthe position of the article 200 or the shortest distance between the twois equal to or less than a reference value, the criterion is determinedto be satisfied (Step S228).

Then, when the determination in Step S228 is Yes, the output unit 120deduces the article 200 taken out by the person (Step S230). Processingperformed in Step S230 is similar to the processing performed in StepS208 in FIG. 5 . On the other hand, when the determination in Step S224is No, the output unit 120 performs alert processing (Step S232).Processing performed in Step S232 is similar to the processing performedin Step S210 in FIG. 5 . The present example embodiment also improvesdetermination precision of an article 200 taken out from a shelf 20,similarly to the first example embodiment. Further, the articleinformation deduction apparatus 10 uses not only a relation between theheight of a hand and shelf position information (that is, a relation ina height direction) but also a relation between the direction of thehand and the position of an article 200 (that is, a relation in ahorizontal plane) in deduction of an article 200. Therefore,determination precision of an article 200 taken out from a shelf 20 isfurther improved.

Fourth Example Embodiment Functional Configuration Example

FIG. 10 is a diagram illustrating a functional configuration of anarticle information deduction apparatus 10 according to the presentexample embodiment along with a use environment of the articleinformation deduction apparatus 10. The article information deductionapparatus 10 according to the present example embodiment has aconfiguration similar to that of the article information deductionapparatus 10 according to any one of the first to third exampleembodiments except for repeatedly acquiring an image from a first imagecapture unit (hereinafter described as a first image) and determining anarticle 200 by using the first images. FIG. 10 illustrates a casesimilar to the first example embodiment.

An image capture area of the first image capture unit 70 includes atleast part of a shelf-front space being a space in front of shelves 20.Therefore, a first image generated by the first image capture unit 70includes at least part of the shelf-front space and includes an article200 taken out from the shelf 20.

Then, an output unit 120 deduces the article 200 taken out from theshelf 20 by a person by using an image of the article 200 included inthe first image. Specifically, a shelf space allocation informationstorage unit 130 stores a feature value of the article 200 in the imagealong with article determination information. Then, the output unit 120deduces the article 200 by using a result of checking the feature valueagainst the first image.

Operation Example

Processing performed by the article information deduction apparatus 10illustrated in FIG. 10 is as described in the first example embodimentusing FIG. 4 . However, details of processing described in Step S104differs from that in the first example embodiment.

FIG. 11 is a flowchart for illustrating details of Step S104 in thepresent example embodiment. Processing performed in Steps S202, S204,S206, S208, and S210 is as described using FIG. 5 . However, the outputunit 120 also reads a feature value of an article 200 along with articledetermination information in Step S208.

Then, the output unit 120 processes a first image captured within areference time (such as 10 seconds) from a change in the detected valueof a weight sensor 30 and extracts a feature value of an article 200included in the first image. Then, when the extracted feature valuematches the feature value read in Step S208, for example, when the scoreis equal to or greater than a reference value (Step S209: Yes), theoutput unit 120 outputs the article determination information read inStep S208 on an as-is basis. On the other hand, when the feature valuesdo not match each other (Step S209: No), the output unit 120 performsthe alert processing (Step S210).

Note that when the processing described above is applied to the articleinformation deduction apparatus 10 described in the third exampleembodiment, the processing described in Step S209 is performed afterStep S230 in FIG. 9 .

The present example embodiment improves deduction precision of anarticle 200 taken out from a shelf 20 by a person, similarly to thefirst example embodiment. Further, a first image includes the article200 taken out by the person. Then, the output unit 120 in the articleinformation deduction apparatus 10 further verifies the article 200deduced from the detected values of a depth sensor 40 and a weightsensor 30 by using the first image. Accordingly, deduction precision ofan article 200 is further improved.

Fifth Example Embodiment Functional Configuration Example

FIG. 12 is a diagram illustrating a functional configuration of anarticle information deduction apparatus 10 according to the presentexample embodiment along with a use environment of the articleinformation deduction apparatus 10. The article information deductionapparatus 10 according to the present example embodiment has aconfiguration similar to that of the article information deductionapparatus 10 according to any one of the first to fourth exampleembodiments except for repeatedly acquiring an image from a second imagecapture unit 80 (hereinafter described as a second image) anddetermining an article 200 by using the plurality of second images. FIG.12 illustrates a case similar to the fourth example embodiment.

The second image capture unit 80 captures an image of a shelf 20 fromthe front (for example, from diagonally above the front). Therefore, asecond image includes an article 200 placed on a shelf 20. Further, whenthe second image capture unit 80 captures an image of a shelf 20 fromdiagonally above the front, an image of an article 200 positioned deepinside the shelf 20 can also be captured. Then, an output unit 120 inthe article information deduction apparatus 10 deduces an article 200taken out from a shelf 20 by a person by further using a change insecond images. Specifically, the output unit 120 deduces an article 200by using the difference between a second image captured before a depthsensor 40 detects a hand of a person (in other words, before a personenters a shelf-front space) and a second image captured after the depthsensor 40 no longer detects the hand of the person (in other words,after the person leaves the shelf-front space).

Operation Example

Processing performed by the article information deduction apparatus 10illustrated in FIG. 12 is as described in the first example embodimentusing FIG. 4 . However, details of the processing described in Step S104differ from those in the first example embodiment.

FIG. 13 is a flowchart for illustrating an operation example of thearticle information deduction apparatus 10 according to the presentexample embodiment. Processing performed in Steps S202, S204, S206,S208, S209, and S210 is as described using FIG. 11 .

Then, when a feature value of an article 200 included in a first imagematches a feature value of an article read from a shelf space allocationinformation storage unit 130 (Step S209: Yes), the output unit 120 inthe article information deduction apparatus 10 processes a second imageand determines whether a correction based on the second image to articledetermination information read in Step S208 is required (Step S212).When a correction is required (Step S212: Yes), the output unit 120executes the correction (Step S214).

For example, the output unit 120 extracts the difference between asecond image captured before the depth sensor 40 detects a hand of aperson (in other words, before a person enters a shelf-front space) anda second image captured after the depth sensor 40 no longer detects thehand of the person (in other words, after the person leaves theshelf-front space) and, by performing matching processing on thedifference, determines whether an article 200 related to the articledetermination information read in Step S208 is moved to a shelf 20different from a shelf 20 in which the article 200 should primarilyreside. In the processing, the position of the article 200 after themovement is determined by, for example, matching processing using afeature value of the article 200. Then, when the movement is detected(Step S212: Yes), the output unit 120 does not output the articledetermination information. For example, when this function is added tothe second example embodiment, the registered article storage unit 60does not store the article determination information of the article 200(Step S214).

In addition, for each movement pattern of an article 200 by a person,the output unit 120 previously stores a combination of a detectionresult of a weight sensor 30, a detection result of the depth sensor 40,and a processing result of a second image. Then, when a resultcorresponding to a combination is detected, the output unit 120 deducesthat a movement pattern related to the combination has occurred.

On the other hand, when a correction is not required (Step S212: No),the output unit 120 outputs the article determination information readin Step S208.

Then, for example, the article determination information is used forcheckout processing of a product in the store, as described in thesecond example embodiment.

The present example embodiment improves deduction precision of anarticle 200 taken out from a shelf 20 by a person, similarly to thefirst example embodiment. Further, the output unit 120 in the articleinformation deduction apparatus 10 determines an article 200 movedwithin shelves 20. Therefore, when there is an article 200 moved withinshelves 20 by a person, false recognition that the person has taken outthe article 200 can be restrained.

While the example embodiments of the present invention have beendescribed above with reference to the drawings, the drawings areexemplifications of the present invention, and various configurationsother than those described above may be employed.

Further, while a plurality of processes (processing) are described in asequential order in each of a plurality of flowcharts used in theaforementioned description, an execution order of processes executed ineach example embodiment is not limited to the described order. An orderof the illustrated processes may be modified without affecting thecontents in each example embodiment. Further, the aforementioned exampleembodiments may be combined without contradicting one another.

The aforementioned example embodiments may also be described in whole orin part as the following supplementary notes but are not limitedthereto.

-   -   1. An article deduction apparatus including:        -   an acquisition unit that acquires weight change data being            data based on a change in a detected value of a weight            sensor provided on a shelf on which a plurality of articles            can be placed and movement data indicating a movement of a            hand of a person positioned in a shelf-front space being a            space in front of the shelf; and        -   an output unit that outputs article determination            information of the article deduced to be taken out by the            hand, by using the weight change data and the movement data.    -   2. The article deduction apparatus according to aforementioned        1, wherein        -   the acquisition unit generates the movement data by using a            detected value of a depth sensor a detection range of which            includes the shelf-front space, and,        -   when a relation between a height of a shelf in which a            change in a detected value of the weight sensor has occurred            and a detected value of a depth sensor that can acquire the            movement data satisfies a criterion, the output unit outputs            the article determination information associated with the            shelf    -   3. The article deduction apparatus according to aforementioned        2, wherein        -   a plurality of shelves with different heights exist,        -   at least one piece of the article determination information            is associated with each of the plurality of shelves, and        -   the weight change data indicate a variation in a weight for            each of the plurality of shelves.    -   4. The article deduction apparatus according to any one of        aforementioned 1 to 3, wherein        -   the output unit outputs the article determination            information associated with, out of a plurality of partial            areas of the shelf, the partial area in which a change in a            weight satisfies a criterion.    -   5. The article deduction apparatus according to any one of        aforementioned 1 to 4, further including        -   a storage processing unit that causes a storage to store the            article determination information output by the output unit            in association with person determination information for            determining the person.    -   6. The article deduction apparatus according to aforementioned        5, wherein        -   the storage processing unit acquires the person            determination information from a person tracking apparatus            tracking a movement of the person.    -   7. The article deduction apparatus according to any one of        aforementioned 1 to 6, wherein        -   the acquisition unit repeatedly acquires a first image being            an image including at least part of the shelf-front space,            and        -   the output unit deduces the article taken out by the hand,            by further using an image of the article included in the            first image.    -   8. The article deduction apparatus according to any one of        aforementioned 2 to 6, wherein        -   the acquisition unit repeatedly acquires a second image            being an image of the shelf captured from a front, and        -   the output unit determines the article determination            information of the article taken out by the hand, by further            using a change in the second image.    -   9. The article deduction apparatus according to any one of        aforementioned 1 to 8, wherein        -   a plurality of weight sensors are provided separately from            one another on the shelf, and        -   the acquisition unit generates the weight change data by            using detected values of the plurality of weight sensors.    -   10. The article deduction apparatus according to any one of        aforementioned 1 to 9, wherein        -   the shelf is installed in a store,        -   the person is a customer, and        -   the article deduction apparatus further includes:            -   a checkout processing unit that performs checkout                processing by using the article determination                information output by the output unit; and            -   an electronic receipt output unit that outputs an                electronic receipt based on the checkout processing.    -   11. An article deduction method including, by a computer:        -   acquiring weight change data being data based on a change in            a detected value of a weight sensor provided on a shelf on            which a plurality of articles can be placed and movement            data indicating a movement of a hand of a person positioned            in a shelf-front space being a space in front of the shelf;            and        -   outputting article determination information of the article            deduced to be taken out by the hand, by using the weight            change data and the movement data.    -   12. The article deduction method according to aforementioned 11,        further including, by the computer:        -   generating the movement data by using a detected value of a            depth sensor a detection range of which includes the            shelf-front space; and,        -   when a relation between a height of a shelf in which a            change in a detected value of the weight sensor has occurred            and a detected value of a depth sensor that can acquire the            movement data satisfies a criterion, outputting the article            determination information associated with the shelf    -   13. The article deduction method according to aforementioned 12,        wherein        -   a plurality of shelves with different heights exist,        -   at least one piece of the article determination information            is associated with each of the plurality of shelves, and        -   the weight change data indicate a variation in a weight for            each of the plurality of shelves.    -   14. The article deduction method according to any one of        aforementioned 11 to 13, further including, by the computer,        -   outputting the article determination information associated            with, out of a plurality of partial areas of the shelf, the            partial area in which a change in a weight satisfies a            criterion.    -   15. The article deduction method according to any one of        aforementioned 11 to 14, further including, by the computer,        -   causing a storage to store the output article determination            information in association with person determination            information for determining the person.    -   16. The article deduction method according to aforementioned 15,        further including, by the computer,        -   acquiring the person determination information from a person            tracking apparatus tracking a movement of the person.    -   17. The article deduction method according to any one of        aforementioned 11 to 16, further including, by the computer:        -   repeatedly acquiring a first image being an image including            at least part of the shelf-front space; and        -   deducing the article taken out by the hand, by further using            an image of the article included in the first image.    -   18. The article deduction method according to any one of        aforementioned 12 to 16, further including, by the computer,        -   repeatedly acquiring a second image being an image of the            shelf captured from a front and determining the article            determination information of the article taken out by the            hand, by further using a change in the second image.    -   19. The article deduction method according to any one of        aforementioned 11 to 18, wherein        -   a plurality of weight sensors are provided separately from            one another on the shelf, and        -   the method further includes, by the computer,            -   generating the weight change data by using detected                values of the plurality of weight sensors.    -   20. The article deduction method according to any one of        aforementioned 11 to 19, wherein        -   the shelf is installed in a store,        -   the person is a customer, and        -   the method further includes, by the computer,            -   performing checkout processing by using the output                article determination information and outputting an                electronic receipt based on the checkout processing.    -   21. A program causing a computer to have:        -   a function of acquiring weight change data being data based            on a change in a detected value of a weight sensor provided            on a shelf on which a plurality of articles can be placed            and movement data indicating a movement of a hand of a            person positioned in a shelf-front space being a space in            front of the shelf; and        -   a function of outputting article determination information            of the article deduced to be taken out by the hand, by using            the weight change data and the movement data.    -   22. The program according to aforementioned 21, further causing        the computer to have:        -   a function of generating the movement data by using a            detected value of a depth sensor a detection range of which            includes the shelf-front space; and        -   a function of, when a relation between a height of a shelf            in which a change in a detected value of the weight sensor            has occurred and a detected value of a depth sensor that can            acquire the movement data satisfies a criterion, outputting            the article determination information associated with the            shelf    -   23. The program according to aforementioned 22, wherein        -   a plurality of shelves with different heights exist,        -   at least one piece of the article determination information            is associated with each of the plurality of shelves, and        -   the weight change data indicate a variation in a weight for            each of the plurality of shelves.    -   24. The program according to any one of aforementioned 21 to 23,        further causing the computer to have        -   a function of outputting the article determination            information associated with, out of a plurality of partial            areas of the shelf, the partial area in which a change in a            weight satisfies a criterion.    -   25. The program according to any one of aforementioned 21 to 24,        further causing the computer to have        -   a function of causing a storage to store the output article            determination information in association with person            determination information for determining the person.    -   26. The program according to aforementioned 25, further causing        the computer to have        -   a function of acquiring the person determination information            from a person tracking apparatus tracking a movement of the            person.    -   27. The program according to any one of aforementioned 21 to 26,        further causing the computer to have:        -   a function of repeatedly acquiring a first image being an            image including at least part of the shelf-front space; and        -   a function of deducing the article taken out by the hand, by            further using an image of the article included in the first            image.    -   28. The program according to any one of aforementioned 22 to 26,        further causing the computer to have        -   a function of repeatedly acquiring a second image being an            image of the shelf captured from a front and determining the            article determination information of the article taken out            by the hand, by further using a change in the second image.    -   29. The program according to any one of aforementioned 21 to 28,        wherein        -   a plurality of weight sensors are provided separately from            one another on the shelf, and        -   the program further causes the computer to have            -   a function of generating the weight change data by using                detected values of the plurality of weight sensors.    -   30. The program according to any one of aforementioned 21 to 29,        wherein        -   the shelf is installed in a store,        -   the person is a customer, and        -   the program further causes the computer to have            -   a function of performing checkout processing by using                the output article determination information and                outputting an electronic receipt based on the checkout                processing.

This application claims priority based on Japanese Patent ApplicationNo. 2019-037829 filed on Mar. 1, 2019, the disclosure of which is herebyincorporated by reference thereto in its entirety.

1. An article deduction apparatus comprising: a memory storinginstructions; and a processor configured to execute the instructions to:acquire weight change data being data based on a change in a detectedvalue of a weight sensor provided on a shelf on which a plurality ofarticles can be placed and movement data indicating a movement of a handof a person positioned in a shelf-front space being a space in front ofthe shelf; output article determination information of the articlededuced to be taken out by the hand, by using the weight change data andthe movement data; and cause a storage to store the articledetermination information in association with person determinationinformation for determining the person, wherein the person determinationinformation is a feature value of the face acquired from an image of aperson.
 2. The article deduction apparatus according to claim 1, whereinthe processor is further configured to execute the instructions to:generate the movement data by using a detected value of a depth sensor adetection range of which includes the shelf-front space; and when arelation between a height of a shelf in which a change in a detectedvalue of the weight sensor has occurred and a detected value of a depthsensor that can acquire the movement data satisfies a criterion, outputthe article determination information associated with the shelf.
 3. Thearticle deduction apparatus according to claim 2, wherein a plurality ofshelves with different heights exist, at least one piece of the articledetermination information is associated with each of the plurality ofshelves, and the weight change data indicate a variation in a weight foreach of the plurality of shelves.
 4. The article deduction apparatusaccording to claim 1, wherein the processor is further configured toexecute the instructions to output the article determination informationassociated with, out of a plurality of partial areas of the shelf, thepartial area in which a change in a weight satisfies a criterion.
 5. Thearticle deduction apparatus according to claim 1, wherein the processoris further configured to execute the instructions to acquire the persondetermination information from a person tracking apparatus tracking amovement of the person.
 6. The article deduction apparatus according toclaim 1, wherein the processor is further configured to execute theinstructions to: repeatedly acquire a first image being an imageincluding at least part of the shelf-front space; and deduce the articletaken out by the hand, by further using an image of the article includedin the first image.
 7. The article deduction apparatus according toclaim 2, wherein the processor is further configured to execute theinstructions to: repeatedly acquire a second image being an image of theshelf captured from a front; and determine the article determinationinformation of the article taken out by the hand, by further using achange in the second image.
 8. The article deduction apparatus accordingto claim 1, wherein a plurality of weight sensors are providedseparately from one another on the shelf, and the processor is furtherconfigured to execute the instructions to generate the weight changedata by using detected values of the plurality of weight sensors.
 9. Thearticle deduction apparatus according to claim 1, wherein the shelf isinstalled in a store, the person is a customer, and the processor isfurther configured to execute the instructions to: perform checkoutprocessing by using the article determination information; and output anelectronic receipt based on the checkout processing.
 10. An articlededuction method comprising, by a computer: acquiring weight change databeing data based on a change in a detected value of a weight sensorprovided on a shelf on which a plurality of articles can be placed andmovement data indicating a movement of a hand of a person positioned ina shelf-front space being a space in front of the shelf; outputtingarticle determination information of the article deduced to be taken outby the hand, by using the weight change data and the movement data; andcausing a storage to store the article determination information inassociation with person determination information for determining theperson, wherein the person determination information is a feature valueof the face acquired from an image of a person.
 11. The articlededuction method according to claim 10, further comprising: generatingthe movement data by using a detected value of a depth sensor adetection range of which includes the shelf-front space; and when arelation between a height of a shelf in which a change in a detectedvalue of the weight sensor has occurred and a detected value of a depthsensor that can acquire the movement data satisfies a criterion,outputting the article determination information associated with theshelf.
 12. The article deduction method according to claim 10, furthercomprising outputting the article determination information associatedwith, out of a plurality of partial areas of the shelf, the partial areain which a change in a weight satisfies a criterion.
 13. The articlededuction method according to claim 10, further comprising acquiring theperson determination information from a person tracking apparatustracking a movement of the person.
 14. The article deduction methodaccording to claim 10, further comprising: repeatedly acquiring a firstimage being an image including at least part of the shelf-front space;and deducing the article taken out by the hand, by further using animage of the article included in the first image.
 15. The articlededuction method according to claim 10, wherein a plurality of weightsensors are provided separately from one another on the shelf, and themethod further comprises generating the weight change data by usingdetected values of the plurality of weight sensors.
 16. A non-transitorycomputer-readable medium storing a program for causing a computer toperform operations, the operations comprising: acquiring weight changedata being data based on a change in a detected value of a weight sensorprovided on a shelf on which a plurality of articles can be placed andmovement data indicating a movement of a hand of a person positioned ina shelf-front space being a space in front of the shelf; outputtingarticle determination information of the article deduced to be taken outby the hand, by using the weight change data and the movement data; andcausing a storage to store the article determination information inassociation with person determination information for determining theperson, wherein the person determination information is a feature valueof the face acquired from an image of a person.
 17. The non-transitorycomputer-readable medium according to claim 16, wherein the operationsfurther comprise: generating the movement data by using a detected valueof a depth sensor a detection range of which includes the shelf-frontspace; and, when a relation between a height of a shelf in which achange in a detected value of the weight sensor has occurred and adetected value of a depth sensor that can acquire the movement datasatisfies a criterion, outputting the article determination informationassociated with the shelf.
 18. The non-transitory computer-readablemedium according to claim 16, wherein the operations further compriseoutputting the article determination information associated with, out ofa plurality of partial areas of the shelf, the partial area in which achange in a weight satisfies a criterion.
 19. The non-transitorycomputer-readable medium according to claim 16, wherein the operationsfurther comprise acquiring the person determination information from aperson tracking apparatus tracking a movement of the person.
 20. Thenon-transitory computer-readable medium according to claim 16, whereinthe operations further comprise: repeatedly acquiring a first imagebeing an image including at least part of the shelf-front space; anddeducing the article taken out by the hand, by further using an image ofthe article included in the first image.